1. Field of the Invention
The present invention is in the field of 3-D volumetric X-ray imaging, and, in particular, is directed to an automated method to measure bone density and structure of the proximal femur without operator interaction.
2. Description of the Related Art
Several diagnostic 3-D X-ray imaging devices are used in medicine to measure bone density of the hip. These imaging devices to which this invention is directed provide a set of volumetric X-ray images acquired from multiple projection angles, which allow reconstruction of images in various planes. Such devices include: dual and single energy CT scanners, rotational G-arms, X-ray tomosynthesis and 3-D DXA (dual-energy X-ray absorptiometry), in which the X-ray source is moved to provide various projections, such as the Hologic 3-D DXA device in development. In addition to bone density, other bone measurements are of interest, including cortical and trabecular bone volume, density and mass, neck cross-sectional area, neck length and angle, finite element analysis, and the like. Accurate and precise measures of bone densities of the neck and total hip regions of interest (ROls) and their change with disease conditions or therapy has great value in detecting and treating osteoporosis. The methods disclosed herein provide improved accuracy, precision and greater ease of use for this important application.
Prior art methods have used CT scanners for bone mineral density (BMD) measurements in quantitative computerized tomography (QCT) by the use of calibration phantoms scanned simultaneously with the patient (simultaneous calibration). Such phantoms have been used for years for spinal vertebral BMD measurements and only in recent years have been used for hip BMD. Representative prior art methods are disclosed in U.S. Pat. No. 4,233,507 to Volz, U.S. Pat. No. 4,233,507 to Arnold, U.S. Pat. No. 5,335,260 to Arnold, and others, which are specific for spine measurements.
U.S. Pat. No. 6,990,922 to Arnold discloses a method for hybrid calibration using simultaneous phantom calibration along with internal tissue references of the individual patient. U.S. Pat. No. 6,990,222 is incorporated by reference herein in its entirety. Bone density measurements are known to vary significantly with different devices, over time and between different institutions, patient body compositions, imaging techniques, and, in particular, with patient positioning in hip measurements. The complicated 3-D anatomical shape, density and structure of the proximal femur make hip BMD measurements subject to variability and loss of precision with current methods. Prior art BMD methods are not applicable to the measurement of the much different anatomy of the hip. All prior art methods to our knowledge require the operator to make subjective decisions and to manually mark specific regions for measurement, or to manually mark start points for semi-automatic methods. Operator decisions and interactions are known to vary over time and between operators resulting in a loss of long term precision. Patients under drug therapy may expect to see 1 to 4% increases in BMD over the course of a year or longer of treatment. Therefore it is important to have sufficiently high precision, which will allow the clinician to reliably detect changes of this magnitude in these time periods. Prior art methods have serious limitations in achieving the desired long term precision.
Recognizing these limitations, others have reported attempts at automated methods and advanced semi-automated methods to achieve higher precisions. The most advanced methods appear to have been reported by Kang and Kang et. al in Y. Kang, Quantitative computed tomography (QCT) of the proximal femur, Inst. of Med Physics. Erlangen, Univ. of Erlangen, 2003, Y. Kang, K. Engelke, W A Kalender, A new accurate and precise 3-D segmentation method for skeletal structures in volumetric CT data, IEEE Trans Med Imaging, 2003; 22:586-98, Y. Kang, K. Engelke, W A Kalender, Interactive 3D editing tools for image segmentation, Med Image Anal, 2004, 8:35-46, Y. Kang, K. Engelke, C Fuchs, W A Kalender, An anatomic coordinate system of the femoral neck for highly reproducible BMD measurements using 3D QCT, Comput Med Imaging Graph 2005, Oct., 29(7):533-41, Epub 2005 Sep. 6, and T F Lang, G Guglielmi, C van Kuijk, A De Serio, M Cammisa, and H K Genant, Measurement of bone mineral density at the spine and proximal femur by volumetric quantitative computed tomography and dual-energy X-ray absorptiometry in elderly women with and without vertebral fractures, Bone, 2002 Jan., 30(1):247-50. These reported methods still require manual interactions by the operator with the images. This retains some elements of variability by the operator resulting in variable results and long term precision loss. Some of these software methods used raw Hounsfield Units (HU) and the proposed segmentation methods used single thresholds.
Since the CT numbers (HU units) are estimates of the X-ray attenuation coefficients of tissue relative to water, they fail to be truly quantitative for several reasons. The attenuation coefficients are photon energy dependent, and the X-ray beam energy spectra are not measured or known for individual patients. Further, there exist differing beam energy spectra in each image, i.e., a unique spectrum for each path length through the patient, and seen at a particular detector element and creating a unique spectrum for each view through the patient. The beam spectrum changes with the thickness and composition of tissues in the path length. These differ significantly from the shape and varied composition of real patients. Image pixel intensities vary from image to image, and are dependent on table height, position of the beam, scanner drift, tube changes, manufacturer's reconstruction software, body thickness and volume, field of view, etc.
Quantitative CT measurements of the hip with currently available commercial systems are typically facilitated by placement of a Region of Interest (ROI) within specific areas of the image to be measured, or the placement of markers at specific locations. A representative commercial system is from Mindways, Inc. The ROI or cursor marker is usually shown on a video screen as a bright line or pointer which has known X and Y locations in the image pixel matrix. The marker or ROI may be adjustable for size and/or shape and positioned by the operator in the target area on 2-D or 3-D reformatted images, by manually moving the ROI or marker under cursor control from a keyboard, by light pen or by mouse. Such manual procedures are tedious and time consuming, as well as prone to error and non-reproducibility in exact positioning. In addition, because many objects in the image, such as the trochanter or neck have complex shapes and irregular margins, a fixed geometry ROI or marker will cause errors, which can be quite large and variable and difficult to evaluate over long time periods.
Typically, the computer software uses thresholding to aid in identifying bone edges. For example, pixels anywhere in the image with HU>200 might be identified as the cortical bone edge. The operator may be required to manually place a pointer or line marker on or near the lesser trochanter or the upper end of the femoral neck region. Even though this significantly aids in locating and segmentation the bone regions, the operator, by manually placing the search marker on a 2-D representation of a complex 3-D object creates variations which reduce precision. The operator must use judgment in placing the marks or ROIs, which can lead to errors and loss of reproducibility on follow up scans attributable to human error. The ability to monitor changes in BMD is thus degraded. The automatic software methods here disclosed provide much faster exam times, more reproducible segmentations resulting in higher precision measurements.